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Bureau of Mines Information Circular/1987 



MgO Filtration Research 



By D. N. Tallman and J. E. Pahlman 



UNITED STATES DEPARTMENT OF THE INTERIOR 



Information Circular 9138 

// 



MgO Filtration Research 



By D. N. Tallman and J. E. Pahlman 




UNITED STATES DEPARTMENT OF THE INTERIOR 

Donald Paul Hodel, Secretary 

BUREAU OF MINES 
Robert C. Horton, Director 




x^ 6 



Library of Congress Cataloging in Publication Data: 



Tallman, Daniel N. 

MgO filtration research. 

(Bureau of Mines information circular; 9138) 

Bibliography: p. 30. 

Supt. of Docs, no.: I 28.27: 9138. 

1. Filters and filtration. 2. Magnesia. 3. Mineral industries— Water-supply. 4. 
Water— Purification— Filtration. 5. Mine drainage. I. Pahlman, J. E. (John E.). II. Title. 
III. Series: Information circular (United States. Bureau of Mines); 9138. 



IM295JJ4-^ [TN535] 



622 s 



[622'.5] 



87-600009 



CONTENTS 

Page 

Abstract 1 

Introduction 2 

Background 2 

Filtration mechanisms 2 

Transient behavior 4 

Filtration indices 5 

Contact filtration of asbestos fibers 6 

Granular bed filtration 7 

Synthetic suspensions 8 

Filtration of kaolin 8 

Filtration of milled sand 10 

Use of polymer f locculants. 10 

Kaolin filtration 10 

Filtration of metal precipitates 12 

Filtration with mixed MgO-sand beds 13 

Applications 13 

Steel mill cooling water 13 

Process water from magneite benef iciation 14 

Process water from flotation of iron ore 15 

Mississippi River water 15 

Process water for cutting granite 15 

Engineering aspects 17 

Backwashing of MgO filters 17 

Attrition of MgO filters during backwashing 21 

Poisoning of MgO filters by heavy metals 23 

Filtration parameters 24 

Effect of surface charge and particle shape on filtration 24 

Removal and head loss coefficients 25 

pH and chemical effects 27 

Scale formation and mudballing 28 

Summary and conclusions 29 

References 30 

Appendix. — Nomenclature 31 

ILLUSTRATIONS 

1. Transient behavior typical of granular bed filtration 4 

2. Filtration of amphibole asbestos by granular MgO and sand filters with 

and without alum pretreatment 8 

3. Filtration with mixed MgO-sand filters 13 

4. Filtration of granite-cutting process water 16 

5. Bed expansion of MgO versus flow velocity 19 

6. Optimum bed porosities calculated from optium Reynolds number 21 

7. Binding of MgO filters 22 

8. Effects of dissolved heavy metals on MgO filtration 23 

9. Cemented MgO chunks containing anthracite grains 28 

TABLES 

1. Dimensionless filtration parameters 3 

2. Contact filtration of asbestos 7 

3. Filtration of synthetic suspensions 9 



ii 



TABLES — Continued 



Page 



4. Filtration with polymer f locculants 

5. Filtration of steel mill cooling water 

6. Filtration of iron ore processing water , 

7 . Chemical analysis of process water 

8. Fluidization results , 

9. Durability study 

10. Effects of filter medium surface charge and particle shape on kaolin 

removal 

11. Head loss and removal coefficients of MgO and sand filters for the 

filtration of kaolin 

12. Effect of influent pH on filtration of kaolin suspension flocculated 

with Al 3+ and Fe 3+ salts 



11 


14 


15 


17 


20 


21 


25 


26 


27 





UNIT OF MEASURE ABBREVIATIONS 


USED IN THIS 


REPORT 


°c 


degree Celsius 


L/s 


liter per second 


cal/(mol 


deg) calorie per mol 
per degree 


m 


meter 






mg/L 


milligram per 


cm 


centimeter 




liter 


cm 3 


cubic centimeter 


min 


minute 


cm H 2 


centimeter water 
(pressure) 


mm 


millimeter 






y m 


micrometer 


cm 3 /g 


cubic centimeter 








per gram 


ymho 


micromho 


cm/s 


centimeter per 


m/s 2 


meter per second 




second 




per second 


eV 


electron volt 


m 2 /s 


square meter per 
second 


g 


gram 










mV 


millivolt 


g/cm 3 


gram per cubic 








centimeter 


NTU 


nephelometric 
turbidity unit 


h 


hour 










pet 


percent 


K 


kelvin 










ppm 


part per million 


kg/m 3 


kilogram per cubic 








meter 


r/min 


revolutions per 
minute 


kg/(m*s) 


kilogram per meter 








per second 


s 


second 


L 


liter 


vol pet 


volume percent 


L/cm 2 


liter per square 
centimeter 


wt pet 


weight percent 






yr 


year 


L/min 


liter per minute 







MgO FILTRATION RESEARCH 



By D. N. Tallman 1 and J. E. Pahlman 2 



ABSTRACT 

The Bureau of Mines has completed 4 yr of deep-bed filtration research 
comparing the efficiencies of granular magnesium oxide (MgO) and conven- 
tional filter sand in single- and dual-medium filters when filtering 
mineral-processing and mine waters. Bench and field evaluation tests 
were conducted using water types ranging from synthetic suspensions of 
asbestos, kaolin, metal hydroxides, and milled sand to process waters 
from magnetite benef iciation, iron ore flotation, granite cutting, and a 
steel mill. Even though the turbidity reductions were similiar, MgO 
filters were found to be advantageous when filtering water pretreated 
with alum because the volume throughput before breakthrough (turbidity 
> 1 NTU unit) was much more for the MgO filter than for the sand filter. 
Reduced head loss owing to the greater porosity of the MgO filter beds 
is potentially the most beneficial advantage in employing MgO as the 
filter medium, especially when filtering water pretreated with polymer 
flocculants. Granular MgO (periclase) is durable and can be backwashed 
like sand. It is compatible with anthracite in a dual-medium filter and 
apparently is not poisoned by dissolved metals in the process water. No 
single solid-removal mechanism could be identified for the improved fil- 
tration observed with granular MgO. 

1 Research chemist, Twin Cities Research Center, Bureau of Mines, Minneapolis, MN 
(now with Econ Laboratories, Eagan, MN). 

^Supervisory physical scientist, Twin Cities Research Center, Bureau of Mines, Min- 
neapolis, MN. 



INTRODUCTION 



Suspended solids are a common impurity 
in mine water. Mines rely mainly on 
flocculation and settling for solid re- 
moval, but this can be unreliable owing 
to seasonal variation in water tempera- 
ture, runoff, and changes in the charac- 
ter of ores being mined. Filtration is 
often needed to provide sufficiently pure 
water to meet mineral processing require- 
ments and/or statutory effluent limits. 
Although recyling decreases the volume of 
discharge needing treatment, it can ad- 
versely affect plant performance unless 
the return water is treated to keep con- 
taminants from reaching unacceptable 
levels of concentration. 

The Bureau of Mines has completed 4 yr 
of research on improving filtration of 
mine and mineral-processing water using 
MgO as the filter medium in contact and 
deep-bed filters. The initial phase of 
work resulted from a previous study of 
the surface charge of asbestos fibers in 
water CO* 3 Numerous candidate materials 
(sand, calcite, diatomaceous earth, ac- 
idic alumina, basic alumina, microcrys- 
talline cellulose, magnesium carbonate, 
and activated carbon) were tested for re- 
moving asbestos fibers from water by con- 
tact filtration, a process that required 
no pretreatment of the water and that 
used shallow beds of fine filter media. 
MgO filter media gave the best removal. 
The superior performance of MgO was at- 
tributed to its positive surface charge 
(2^). The next phase of research was the 
application of MgO to filtration of other 
suspended solids occurring in natural 
waters. Bench-filtration tests that 



compared MgO and filter sand were per- 
formed on synthetic suspensions and on 
mine-water samples (_2-3)« In these tests 
granular materials were used for practi- 
cal reasons such as achieving adequate 
solid-loading capacity and reducing pres- 
sure drop through the filters. Floccula- 
tion with alum improved filtration with 
the granular media, and MgO generally 
outperformed sand. Field tests were run 
to validate bench-scale tests on mine 
water (4^« 

The remaining phase of research dealt 
with practical engineering aspects of us- 
ing MgO filters, such as f luidization, 
backwashing, and durability. Attempts to 
derive a model for MgO bed expansion were 
unsuccessful because there appears to be 
a transition in the expansion behavior of 
the MgO for particles between 0.5 and 
1.0 mm. MgO was found to be compatible 
with anthracite but not with sand in 
dual-medium filters as the anthracite and 
MgO were easily restratified by backwash- 
ing. Granular MgO possesses the neces- 
sary durability to be a filter medium and 
was apparently not poisoned by dissolved 
metals in the process water. The MgO 
filters were tolerent to moderate levels 
of calcium hardness and carbonate alka- 
linity, provided adequate backwashing 
with air scour was available. Cementa- 
tion of MgO grains with each other or 
with anthracite grains was observed with 
scale formation in the filters. Descrip- 
tions of each phase of research and dis- 
cussion of pertinent results are pre- 
sented in this report. 



BACKGROUND 



FILTRATION MECHANISMS 

A detailed theoretical discussion of 
filtration mechanisms as they pertain to 
MgO filtration is beyond the scope of 
this paper. Reviews of the theory of 
deep-bed filtration are available in the 

3 Underlined numbers in parentheses re- 
fer to items in the list of references 
preceding the appendix. 



literature (_5-7)« A brief examination of 
relevant filtration mechanisms, however, 
is helpful for understanding the filtra- 
tion results presented herein. 

In deep-bed filtration, filter pores 
are usually large compared with the size 
of the particles being filtered. Clear- 
ly, forces other than straining must ac- 
count for particle retention (_5). Trans- 
port and attachment steps are both 
important in the capture of small 



suspended particles. Flow is usually 
laminar, so forces must act on a particle 
to move it across streamlines into close 
proximity with the surface of the filter 
medium where attachment forces operate. 

The main forces considered in particle 
transport are gravitational, diffusional, 
hydrodynamic, and inertial forces (4~5)« 
Surface forces that affect attachment are 
of mainly two kinds, the molecular dis- 
persion force (London van-der-Waals 
force) and the double-ionic-layer force, 
which is mainly due to surface charge 
(6_). Particle interception is really 
neither a transport mechanism nor an at- 
tractive force, but it is the final step 
in particle capture in any case. The net 
effect of all these forces will determine 
the overall removal efficiency of the 
filter. Contributions to particle col- 
lection by each type of force can be 
estimated using the dimensionless param- 
eters given in table 1. In general, it 
can be seen that the size of the particle 



to be captured is the single most impor- 
tant variable; increasing the parti- 
cle size will enhance all collection 
mechanisms except diffusion and London 
van-der-Waals forces. For particles 
smaller than 1 ym, surface charge, ionic 
strength, and diffusion are dominant cap- 
ture mechanisms, while interception 
and/or straining becomes dominant above 
10 to 100 ym. For particles with sizes 
between 1 and 10 ym, mixed capture mecha- 
nisms are observed. Overall collector 
efficiency is at a minimum for particles 
of about 1-ym diam; increasing particle 
size by flocculation results in better 
collection. Flocculation also acts to 
decrease surface charge on the particle 
so that surface charge effects are re- 
duced. At high ionic strength, the 
ionic-double-layer thickness (l/<) is 
minimal. This also reduces surface- 
charge effects. 

Particle detachment is especially im- 
portant in cleaning filters, but also 



TABLE 1. - Dimensionless filtration parameters 



Parameter Typical range 



Formula 



Comments 









ATTACHMENT MECHANISMS 


n dl 


10°-10 5 


<a D , where 


Dimensionless double-layer-thick- 








e d kT I m J Z J 
1 


1/2 


ness effect of ionic strength 






K = 




versus conductivity. 


n E i 


10 _1 -10 3 


£d<(^p 2 + ip m 2 )/12iryv 


Electrokinetic group 1: elec- 
trical versus shear forces. 


N E 2 


-1 to +1 


2<Mm/(iJ'p 2 + ^ 2 ) 


Electrokinetic group 2: "parity" 
group; - = favorable, 
+ = unfavorable interaction. 


n L o 


io- 5 -io -2 


h/9iry a p 2 v 


London group: London-van-der- 
Waals forces-shear forces. 







INTERCEPTION AND STRAINING 


Nr 


io-Mo" 1 


dp/d m 


Relative-size group. 



TRANSPORT MECHANISMS 








-14 


ga p 2 (p p -pf )/18yv 
RT 


Gravity group: settling velocity- 
approach velocity, 
dimensionless . 


1/Pe 


10" 


8_ 10 -5 


Inverse of Peclet number: ratio 
of diffusion number to approach 


3iryd p d m 










velocity. 


Re 




~1 


vdpg/y = vdp/v 


Reynolds number: characterizes 
hydrodynamic; usually laminar. 



Sources: Rajagopulan and Tien (7) and Ives (5) 



during filtration, where increases in 
flow rate will create proportionately 
higher shear forces that can dislodge de- 
posited solids and cause breakthrough. 
Beds with large filter-medium grains and 
large porosity will have less head loss 
and will be more resistant to scouring 
and subsequent breakthrough (4). 

TRANSIENT BEHAVIOR 

To get a complete description of a fil- 
tration process, one needs to obtain a 
record of the pressure drop (both across 
the bed and within the bed), filtrate 
quality, and flow rate as they vary with 
time. Idealized versions of typical 
kinds of head-loss and turbidity behavior 
are illustrated in figure 1 by curves A 
and A' for deep-bed filtration and by 
curves B and B' for surface straining or 
cake filtration. Filtration is a dynamic 
process with pressure and turbidity fluc- 
tuating as channels become clogged with 
deposits and reopened by scouring. As 
filtration progresses, more material be- 
comes lodged in the filter, the porosity 
decreases, and as a result head loss in- 
creases with time. This manifests itself 
as a rise in the water level above a 
gravity filter or as increased gauge 
pressure in a pressure filter. At con- 
stant loading, the deposit in the filter 
grows at a steady rate, and the head 
above the filter increases almost linear- 
ly with time (curve A y fig. 1). Changes 
in either influent flow rate or solids 
concentration will have a corresponding 
effect on head loss. This is the ex- 
pected pattern in deep-bed filtration. 
Often the suspended solids are actually 
removed at the surface of the bed by 
straining. As a result of this phenom- 
enon, a cake forms and pressure begins to 
increase exponentially, as in curve B of 
figure 1. Filtrate turbidity will gener- 
ally be very low, as in curve B' . Sur- 
face or cake filtration is inefficient, 
because designed increases in allowable 
head loss result in diminishing gains in 
filtrate volume before backwashing is 
necessary. Poor design, changes in solid 
loading, or atrrition of the medium 



are the usual causes of excessive rates 
of head loss. 

In deep-bed filtration the filtrate 
turbidity initially decreases slightly 
and then levels out before breakthrough 
(curve A' of figure 1). Up to a point, 
material deposited in the filter improves 
solid capture, but then a critical point 
is reached where the reduction in poros- 
ity and the resulting increased shear 
rates cause a decrease in the efficiency 
of solid removal. In fact, deposits are 
often dislodged and then trapped deeper 
in the filter. This scour-deposit mech- 
anism was postulated by Mints (5) when he 
observed that particles appearing in the 
filtrate at breakthrough were larger than 
those in the influent, leading to the 
assumption that they were actually floes 
of deposited material. Onset of break- 
through may manifest itself as increased 
fluctuation in the filtrate turbidity and 
is most easily observed with a 
turbidimeter-recorder setup. In Bureau 
filtration tests, increased fluctuation 
in the turbidity was usually observed 
prior to consistent increases in turbid- 
ity. This may be a reliable indicator of 
imminent breakthrough. 

FILTRATION INDICES 

Efficient deep-bed filtration is the 
result of a successful compromise between 
filtrate quality goals and minimizing 
head loss. The best filter achieves the 
desired quality at the lowest pumping 
cost. Flocculant dosage and mixing, 
filter-grain size, flow rate, and depth 
are all interdependent; sometimes adjust- 
ments in one or more of these variables 
become necessary due to variations in in- 
fluent composition. Numerous attempts 
have been made to describe the perfor- 
mance of a filter quantitatively, in 
terms of both filtrate quality and head 
loss, with a single number or index 
(_5, 8). One of the simpler and more com- 
monly used indices is the f ilterability 
index (F) given by Ives (_5): 

F = (C/C )(H/vt) = (t/t )(H/V), (1) 



x - 



en 

CO 

O 



Q 

< 

LU 

X 







1 1 


1 


1 
B. 


1 1 








- 












A 


A 1 


- 


- < 




r 

t 






I 


KEY 

A, A' Deep-bed filtration 

B,B' Surface straining or 
cake filtration 

i 






- 




1 1 


B' 

i 



> 



CD 

or 



TIME (t) 
FIGURE 1.— Transient behavior typical of granular bed filtration. 



where C = concentration, 

H = increase in head loss, 

v = filtration rate or approach 
velocity, 

t = time, 

t = filtrate turbidity, 

V = filtrate volume per unit area 
at time t (V = vt), 



and 



C = influent concentration, 
t = influent turbidity. 



The f ilterability index is the product of 
two dimensionless parameters that can be 
represented by residual turbidity and 
head-loss rate. Low values of F indicate 



efficient filtration; effective solid re- 
moval and/or small head loss could con- 
tribute to a low value for F. F could be 
used, for example, by a plant operator 
who needs to adjust plant-water treatment 
to seasonal variations of influent-solid 
loading. Several options such as floccu- 
lant dosage and flow-rate changes would 
be tested on several small-scale filters 
run in parallel. The parameters that re- 
sult in the minimum value of F and still 
meet quality goals can then be tried full 
scale. Comparisons of filter media can 
also be made with F; the filter giving 
the lowest value of F is the best choice 
for a given influent. Other indices are 
available that are similar to F but take 
into account operating limitations on 
head loss and filtrate quality for a par- 
ticular plant (8). 

Higher solids concentrations will in- 
crease H/V, but this is not accounted for 
by F. Comparisons of tests run with 



different solids concentrations require a 
different index that will normalize the 
effect of concentration. The solid cap- 
ture index (SC) measures the amount of 
solid trapped in the filter per unit area 
per unit head loss and is expressed in 
units of concentration (g/cm 3 ). This 
type of index was used by Bauman and 
Cleasby (8) to compare waste water fil- 
tration results at various treatment 
plants and is defined by the following 
equation: 

SC = C (1-C/C )(V/H) 

= C (1-t/t )(V/H). (2) 

Large values of SC are desirable. 

One disadvantage of using filtration 
indices is that different values of H, V, 
and t could give the same value for F or 
SC. For the large number of tests per- 
formed in this study, filtration indices 
provide the only practical means of ana- 
lyzing experimental data. Aside from a 
few figures used to illustrate special 
cases, the f ilterability index, F, and 
solid capture index, SC, have been used 
throughout this review. To offset the 
ambiguity that results from relying on 
filtration indices, the values of t/t 
and V/H are given so that the contribu- 
tion of each parameter can be assessed. 



This is especially important when values 
of either F or SC for two filters are al- 
most equal. 

The values of V and v are also listed 
for further evaluation of results. Gen- 
erally, values of F were calculated for 
the portion of a test preceding break- 
through. After breakthrough, F values 
may actually improve because often there 
is a reduction in head loss that is dis- 
proportionate to average turbidity in- 
crease. Comparison between a filter that 
has broken through and one that has not 
broken through is invalid because the 
former no longer meets quality require- 
ments. Excellent values of F (due to low 
head loss) may be obtained for a filter, 
but breakthrough may be reached so quick- 
ly that it would be impractical to use 
that filter. A ratio of V/v greater than 
21.6 (run length equal to 6 h) should be 
achieved for practical purposes; net pro- 
duction of filtered water declines rapid- 
ly with further decreases in run length 
because more frequent backwashing becomes 
necessary (_9)» In some cases, filtrate 
quality never reaches satisfactory levels 
or may be declining when a run is termi- 
nated because of excessive head loss on 
one of the filters. For these tests, F 
values are based on the entire run, and 
values of V for the two media being com- 
pared should be approximately equal. 



CONTACT FILTRATION OF ASBESTOS FIBERS 



Contact-filtration experiments were 
performed using a number of natural and 
synthetic filter materials. The filters 
were typically a 0.5- to 2.0-cm layer of 
0.10-mm (minus 100- plus 200-mesh) Baker 4 
reagent-grade material supported by a 
layer of coarse sand and cotton. MgO, 
sand, magnesium carbonate, acidic and 
basic alumina, calcite, diatomaceous 
earth, microcrystalline cellulose, and 
activated carbon were all tested against 
suspensions of amosite and crocidolite 
asbestos in distilled water. Amphibole 
and chrysotile asbestos samples were ob- 
tained from the International Union 

^Reference to specific products does 
not imply endorsement by the Bureau of 

Mines. 



Against Cancer (UICC). Ultrasonic and 
mechanical agitation were used to dis- 
perse the asbestos fibers in water. The 
beds were washed with 50 cm 3 of distilled 
water, 15 cm 3 of 1- to 10-ppm suspension 
was added to the next 50-cm 3 aliquot 
passing through the filter, and finally 
the filter was washed with an additional 
50 cm 3 of water. Flow velocities were 
0.07 to 0.15 cm/s under 10- to 20-cm 
gravity head. The entire volume of fil- 
trate was then passed through a 0.45- 
pm-pore-size membrane filter. Fiber 
counts were made on sections of filter 
membrane using a scanning electron micro- 
scope at magnifications of x 1,000 to 
x 5,000. 

Results for the contact filtration ex- 
periments are summarized in table 2. MgO 



TABLE 2. - Contact filtration of asbestos, 
percent removed 



Solid filter medium 

Sand ■ 

Calcite 

Diatomaceous earth . 

Microcrystalline cellulose. 

Alumina, acidic 

Alumina, basic 

MgO 

Carbon 



Amp hi bole 


Chrysotile 








10 


60 


60 


10 


20 


20 


99 


50 


50 


80 


100 


99 


85 


65 



Source: Schiller and Khalafalla (2). 



and acidic alumina were both efficient 
for filtering amphibole asbestos, but 
only MgO could effectively remove both 
amphibole and chrysotile asbestos. These 
results can be explained on the basis of 
surface charge and pH. Surface charge 
on particles in water is pH dependent. 
Charge is acquired owing to selective 
dissolution-adsorption of ions at the 
liquid-solid interface. Amphibole asbes- 
tos and most naturally occurring particu- 
lates are negatively charged in water. 
Adsorption of H + and OH" account for the 
pH dependence; particles generally become 
more negative at higher pH. The isoelec- 
tric point for amphibole asbestos is 
pH 3 to 3.5, and that of chrysotile is 



approximately pH 11. Amphibole asbestos 
has a negative zeta potential of -25 to 
-45 mV in neutral and slightly basic wa- 
ter. Chrysotile has a positive zeta po- 
tential but flocculates in water at high 
pH. MgO is basic and has a positive sur- 
face charge below pH 12, so it is able to 
remove the amphibole asbestos fibers by 
electrokinetic attraction and still re- 
move positively charged chrysotile by 
causing it to flocculate. Acidic alumina 
is also positively charged, but not 
basic, so it collected amphibole asbestos 
but passed the chrysotile because the pH 
of the suspension was not increased 
enough to cause f locculation. 



GRANULAR BED FILTRATION 



The contact filters restricted flow ex- 
cessively and collected too few particles 
to be directly applicable for treating 
water. For practical reasons such as 
solid loading, filtration rate, and 
backwashing (filter regeneration), granu- 
lar filters are used to filter waste 
water. 

The purpose of this phase of work was 
to compare red flint sand and MgO as 
granular filters for removal of asbestos 
and other naturally occurring particu- 
lates. Granular MgO was purchased as 
crushed periclase from Basic Chemical and 
Kaiser. The periclase is made by roast- 
ing MgO (calcining) at a high enough tem- 
perature so that it fuses and becomes in- 
ert ("dead burning"). This product was 
chosen because it was less friable than 
pellets of a more active MgO material. 
Active magnesia such as was used in the 



contact filtration studies is calcined at 
lower temperatures so that much of its 
internal porosity is retained. Conse- 
quently, in changing to a durable granu- 
lar material substantially more surface 
area was lost than would be predicted on 
the basis of gross-particle size. 

Filtrate quality is often measured by 
turbidity (light scattering) rather than 
particle counting because this allows 
real-time monitoring and better control 
of the filtration process. Filtrate tur- 
bidity was therefore used as a measure of 
filtering efficiency in almost all of the 
granular-bed-filtration tests. Initial- 
ly, a comparison was made between parti- 
cle counting with the scanning electron 
microscope and turbidity measurement 
(nephelometric), and the two methods were 
found to agree within experimental error 
of the former. Pressure and turbidity 



were measured at 15-min intervals over 
runs lasting several hours or more. 

It became apparent that granular MgO 
was not nearly as effective for removal 
of asbestos as was the more active MgO 
used in contact filtration. Adequate re- 
moval could be achieved only by adding 
flocculant to the influent. Figure 2 il- 
lustrates how removal rates of both sand 
and MgO filters are improved by the addi- 
tion of 1 ppm of alum (potassium aluminum 
sulfate heptahydrate) to the suspension 
15 min before filtration. Flow velocity 
was 0.5 cm/s. These results indicate 
that forces other than surface charge op- 
erate in these filters. Although the MgO 
gives better removal than sand in the ab- 
sence of alum, both filters benefit by 
the increase in particle size due to 
f locculation. For the 0.71-mm sand and 
MgO used in this test, bed porosities are 
38 and 50 pet, respectively. With f loc- 
culation the sand actually becomes the 
more efficient filter by a small margin, 





i i 
/ 


1 1 1 1 


- 


1.00 


/ ^? ■ 


.7b 


KEY 


- 






.50 




/ Sand 
2 MgO 


- 




rl ^^^~<^ 


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.2b 


11 4 

1 1 


4 Sand with alum 






i I i i 





0.5 



1.0 



1.5 2.0 

TIME, h 



2.5 



3.0 



3.5 



FIGURE 2.— Filtration of amphibole asbestos by granular 
MgO and sand filters with and without alum pretreatment. 



owing to enhanced particle interception 
or mechanical straining. However, the 
increase in pressure drop (head loss) 
across the sand filter occurs from two to 
five times faster than that for the MgO 
filter. In virtually all remaining tests 
flocculant was added before filtration. 



SYNTHETIC SUSPENSIONS 



Standard suspensions of kaolin and 
milled sand were used in many filtration 
tests to achieve maximum reproducibility 
of solution turbidity. Mine water sam- 
ples, in contrast to standard suspen- 
sions, are often complex mixtures of var- 
ious dissolved chemicals and particulates 
that may vary considerably between sam- 
pling and testing. With consistent prep- 
aration procedures, synthetic suspensions 
of known concentrations and reproducible 
turbidities were made. In-mine-water 
sample turbidity was assumed to be pro- 
portional to suspended-solid concentra- 
tion, and actual suspended-solid concen- 
trations were not measured for every 
test. For the synthetic suspensions, it 
was possible to calculate both filter- 
ability (F) and solid-capture (SC) in- 
dexes because suspended-solid concentra- 
tions were known. Only F was determined 
for mine-water samples, but the effect of 
altered influent-solid loadings can be 
estimated from head-sample turbidities. 
The mass of flocculant was not included 
in the calculation of SC, even though al- 
uminum hydroxides could contribute to 
solid loading as a result of using alum 
for f locculation. 



FILTRATION OF KAOLIN 



Results for the filtration of kaolin 
suspensions by 30-cm-deep beds of MgO and 
sand are listed in table 3. Single- 
medium MgO filters are better than sand 
filters by a substantial margin; the val- 
ue of F is about eight to nine times 
smaller and that of SC is about four 
times larger for MgO than for sand. Com- 
parison of tests 1 and 2 demonstrates how 
the effect of suspended-solid concentra- 
tion is minimized by using SC rather than 
F. The higher suspended-solid concentra- 
tion causes a larger rate of head loss 
and consequently increased the value of 
F, but this effect is factored out in SC. 
Using finer sized MgO decreases the ef- 
ficiency of the filter; filtrate quality 
is no better with 0.42-mm MgO, and head 
loss rate is approximately doubled. 
Since shear rates are considerably higher 
In the 0.42-mm MgO, run length was short- 
ened by earlier breakthrough. 

Dual-medium filters were made with a 
15-cm layer of 0.71-mm sand over 30 cm of 
either 0.42-mm MgO or 0.42-mm garnet 
sand. Garnet sand is sometimes used 
as a second or even third layer in 



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10 



multiple-medium filters. The performance 
of the two dual-medium filters is more 
nearly equal than that of the single- 
medium filter. Since in both filters the 
sand (upper) layer removes most of the 
suspended solids and consequently con- 
tributes most to head loss, the filters 
would be expected to be similar. The 
sand-MgO filter is 1.5 to 3 times more 
effcient than the sand-garnet filter. 

Dual-medium filters of anthracite-MgO 
and anthracite-garnet were tested with 
much higher loadings of kaolin. These 
filters were comprised of 50 pet anthra- 
cite and either 50 pet MgO or 50 pet gar- 
net for an overall depth of 30 cm. Al- 
though run lengths were cut in half, a 
large amount of solids were collected by 
these filters. Filtering such high load- 
ings of kaolin is probably impractical 
because filters would be operating at 
<80-pct availability because of the need 
for frequent backwashing. 

FILTRATION OF MILLED SAND 

MgO filters were dramatically better 
than sand filters for filtering milled 
sand flocculated with alum (table 3). 
MgO gives lower F values by a factor of 
10, and SC values are seven to eight 
times larger than for sand. Both filters 
were 42±1 cm deep. With dual-medium fil- 
ters the difference is much less appar- 
ent. The dual-medium filters were 46 cm 
deep, with the top third of the filter 
being the sand layer. F(xl0 5 ) ranges 
from 8.8 to 9.2 for sand-garnet filters 
and from 4.2 to 6.4 for sand-MgO filters. 
Although the variance between values for 
duplicate tests is fairly large, the dif- 
ferences between filter-medium types are 
statistically significant. The mean val- 
ues are 9.0 for F(xl0 5 ) and 12.4 g/cm 3 
for SC for the sand-garnet filter versus 
5.4 and 17.4 g/cm 3 for the sand-MgO fil- 
ter. Filtrate volume at breakthrough for 
the sand-garnet filter is about 60 pet 
that of the sand-MgO filter. The sand- 
MgO filter is 1.4 to 1.6 times better by 
any of these criteria. 

There is remarkable similarity between 
results for the filtration of kaolin and 
milled sand in these tests. Values for 
SC and F are better overall for filtering 



the milled sand. This is 
particle size differences 
suspensions and to the 
loadings of milled sand, 
get a high removal rate 
influent loading. The 
ferences between the 
are quite consistent 
suspensions. 



probably due to 

between the two 

use of higher 

It is easier to 

with increased 

relative dif- 

various filters 

for the two 



USE OF POLYMER FLOCCULANTS 
Kaolin Filtration 

Recent trends in process-water treat- 
ment include the use of organic polymers 
or polyelectrolytes to improve floccula- 
tion and increase filter-loading capaci- 
ty. Often an inorganic salt of aluminum 
(alum) or Fe 3+ is added to destabilize 
colloidal dispersions and create small 
"pin" floes. Then a polymer is added to 
further flocculate the solid into large 
(1- to 10-mm), fast-settling floes. Typ- 
ical dosages of polymer are 0.1 to 
10 ppm, and the amount required is 
strongly dependent on the solids concen- 
tration. Although most of the solids are 
removed effectively by settling, a small 
residual fraction of solids often has to 
be removed by filtration. The choices of 
polymer (cationic, anionic, or nonionic) 
and dosage are usually determined by 
settling tests. Floes created with poly- 
mer are larger and more shear resistant 
than alum-type floes. Coarser media, 
deeper beds, and higher filtration veloc- 
ities are typical of filtration with 
polymer f locculation, and solid-loading 
capacity is usually larger than with alum 
f locculation. 

Sand-MgO and sand-garnet filters were 
tested with a 25-ppm kaolin suspension 
treated with 10 ppm alum and 1.0 ppm Sep- 
aran AP-30, an anionic polymer; the re- 
sults are given in table 4. The best 
filtration was with the sand-garnet fil- 
ter and a filtration velocity of 
0.35 cm/s. The coarser anthracite-sand 
filter gives approximately equal SC, but 
residual turbidity is relatively high: 
t/t = 0.22. The best result for MgO was 
with coarser media and a velocity of 
0.52 cm/s, but in general it can be seen 
that use of polymer actually diminished 



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12 



the filterability of the MgO. Filtration 
indexes for the sand-garnet filter are 
about the same whether polymer or only 
alum was used to flocculate the kaolin. 
Head loss through the sand-MgO filter was 
greatly increased; this occurred almost 
entirely in the MgO (lower) layer. Usu- 
ally the upper layer collects the greater 
share of solids and constricts flow more 
than the lower (finer) layer, and the 
sand and garnet contribute little to the 
observed head loss when they comprise the 
lower layer. The filterability index 
F(xl0 5 ) for MgO was increased from 9.2 
with alum flocculation (table 3, test 9) 
to 220 by using anionic polymer (table 4, 
test 20). Solid capture of the sand-MgO 
filters decreased by a factor of 21. Un- 
der these conditions, MgO did not offer 
any significant advantage over conven- 
tional media. 

Filtration of Metal Precipitates 

Fe 3+ and other base-metal ions are com- 
monly found in mine water. Precipitates 
of these ions as hydrous metal oxides 
present difficult filtration problems be- 
cause of their fragility; they are easily 
disrupted by the shear forces encountered 
in conventional granular-bed filters. 
These precipitates also settle slowly, 
and the voluminous toxic sludge produced 
by settling presents a serious disposal 
problem. Polymer is often added to im- 
prove settling and to aid in dewatering. 

A series of tests were performed to see 
if MgO offered any advantage over conven- 
tional filter media for postsettling fil- 
tration of metal hydroxides. Sand and 
MgO filters were first tested on Fe(0H) 3 
precipitates, produced by bringing a 
100-ppm-FeCl 3 solution to pH 8.7. A 
second test suspension was prepared that 
had 78 ppm Fe 3+ and 10 ppm Mn 2+ as sul- 
fate salts and 37 ppm Mn 7+ as permanga- 
nate at pH 8.0 to 9.0. The Mn 7+ was 
present at about 20 pet excess for oxi- 
dizing the Fe 2+ and Mn 2+ , so the predomi- 
nant species under these conditions were 
Mn0 2 and Fe(0H)3. A similar suspension 
was made by simply oxidizing 11 ppm Fe 2+ 
with 1.7 ppm Mn(VII) at pH 7.5 to 8.5. 
Separan AP-30, an anionic polymer, was 



used to flocculate the precipitates in 
most of the tests. These suspensions 
were made to simulate waste water from a 
western metal mine that contained Mn and 
Fe at approximately these levels. Field 
tests were later run on the actual mine 
effluent. In the mine water treatment 
plant, polymer was used to aid clarifica- 
tion and also for sludge dewatering; no 
additional polymer was added to the water 
being pumped through the small test fil- 
ters, since none was being added to that 
entering the sand filters in service at 
the plant. 

Results for both laboratory and field 
tests are summarized in table 4. Bed 
depths for all tests were 30 cm. Neither 
medium could filter prepared suspensions 
of metal oxides effectively without the 
use of polymer. Field tests and labora- 
tory tests with flocculant were in rea- 
sonable agreement, especially if the re- 
duced head-sample turbidity in the field 
tests is taken into account. During the 
field tests plant water was cleaner than 
normal because the mill operation had 
been suspended and the water being 
treated was diluted by spring runoff. 
Reduced solid loading would result in F 
being lower than predicted from laborato- 
ry tests. The most efficient filtration 
(minimum F) is with 1.7- and 1.8-mm me- 
dia, and the MgO is slightly better than 
equivalently sized sand. In general, 
sand gives slightly better removal rates 
and the MgO has smaller head losses, 
probably owing to the larger porosity of 
the MgO. Surface-charge forces would be 
expected to diminish in importance when 
the filter media and the suspended- 
particle size are large, and because 
flocculation has also essentially neu- 
tralized particle surface charge. The 
stronger and larger floes produced by the 
polymer are retained in the filter mainly 
by gravity or hydrodynamic forces, so the 
two media are essentially equally effec- 
tive. Floes were able to penetrate well 
into both filters, so straining was not 
the dominant removal mechanism. Filter- 
ing of the base metal hydroxides or hy- 
drous oxides, even with the use of pol- 
mer, is fairly inefficient compared with 
filtering particulates such as kaolin. 



13 



- 2 

Q 

OD 

or 



Ld 



< 

CC 



1 1 1 1 1 


1 


KEY 




i I 


9 o 


Sar 


id 






- / • 


% 


sand, 


> 


MgO 


a # y a 


'/ 3 


sand, 


% 


MgO 


rw / / / a 

Fill II 


Mg 
1 







l l 



3 4 5 6 

TIME, h 

FIGURE 3.— Filtration with mixed MgO-sand filters. 



Efficiency might be improved by using 
higher filtration rates and deeper beds 
of coarser media. 

Filtration With Mixed MgO-Sand Beds 

A brief investigation of the possibil- 
ity of using mixed MgO-sand beds was un- 
dertaken. However, as shown in figure 3, 
this does not appear to be feasible be- 
cause of rapid breakthrough with mixed 
beds. The filters were 30-cm beds of 



0.71-mm MgO and/or sand, and the 
filtration velocity was 0.21 cm/s. Be- 
cause of the poor retention of solids, 
head loss decreased with decreasing MgO 
fraction. Values of SC were 4.8, 5.2, 
8.3, and 9.6 g/cm 3 in order of increasing 
sand content, but in this case the use of 
indexes is misleading. The most likely 
reason for the poor retention of kaolin 
by the mixed beds is the reduction in po- 
rosity that results from mixing spherical 
(sand) and angular (MgO) particles. 



APPLICATIONS 



MgO and sand filters were compared in 
field tests at four mines and two 
mineral-processing sites. In addition to 
mine water, MgO was tested on river water 
for its application to municipal-water 
treatment. 

STEEL MILL COOLING WATER 

Large volumes of process water are used 
in secondary production of steel. Much 
of this water is used in the direct-spray 
quenching of billet and becomes contami- 
nated mainly by mill scale and tramp 
oils. The mill scale is removed by set- 
tling primary and secondary scale pits, 
but residual suspended solids clog spray- 
er nozzles and increase abrasion of plant 
piping. Tramp oils are treated by skim- 
ming and emulsif iction with surfactants. 



The treated water passes through a cool- 
ing tower before returning to the plant. 
Several samples of return water were 
filtered in laboratory tests before field 
testing began. Results for both field 
and laboratory tests are shown in table 
5. The process water had high levels of 
dissolved solids, and suspended particles 
had weakly negative zeta potentials, but 
these could not be measured accurately 
owing to the high conductivity of the wa- 
ter. Jar tests showed that 30 ppm alum 
gave optimum settling. Results of the 
bench tests indicated that the dual- 
medium filters were not significantly 
better than single-medium filters, and 
that the MgO and anthracite-MgO filters 
were able to filter two to three times 
more water before breakthrough than the 
sand or anthracite-garnet filters. 



14 



TABLE 5. - Filtration of steel mill cooling water 



Test 



Filter medium (d m ) 



NTU 



t/t 



V, 
L/cm 2 



v, 
cm/s 



V/H 



F 
(xlO 5 ) 



LABORATORY TESTS 





1. 




1. 


38 


0. 




0. 




0. 



3-mm anthracite, 0.71-mm 
3-mm anthracite, 0.71-mm 

7 1— mm MgO 

7 1-mm sand 

7 1 -mm MgO 



sand* • • 
MgO .... 



13.3 

19.3 

24 

27 

22 



0.038 
.018 
.015 
.030 
.011 



3.4 
6.7 
7.4 
2.4 
6.2 



0.34 
.34 
.34 
.34 
.34 



106 
91 

106 
57 
31 



36 
20 
14 
53 
35 



FIELD TESTS 



41, 

42. 
43. 
44. 
45. 
46. 



0.71-mm MgO 

0. 7 1-mm sand 

0.71-mm MgO 

0. 7 1-mm sand 

0.71-mm MgO 

0. 7 1-mm sand 

0.71-mm MgO 

0. 7 1-mm sand 

0.71-mm MgO 

0. 7 1-mm sand 

1.3-mm anthracite, 
1.3-mm anthracite, 



0. 7 1-mm 
0. 7 1-mm 



MgO .... 

sand. • • 




0.35 


13 


.34 


3.1 


.33 


18 


.33 


8.7 


.21 


38 


.21 


42 


.18 


>59 


.15 


33 


.23 


30 


.23 


31 


.24 


41 


.24 


39 



120 
1,800 

130 

620 
47 
53 

<42 
76 
63 
57 
52 
63 



Values of F(xl0 5 ) are 14 and 35 for MgO 
and 53 for sand, while differences be- 
tween the dual-medium filters are less 
pronounced. 

In the field mainly single-medium fil- 
ters were tested, and flow rate was the 
only variable that was manipulated. In 
general, the field and laboratory tests 
are in agreement. Filtration velocities 
had to be reduced from 0.34 to 0.21 cm/s 
to get F values roughly equivalent to 
those from bench tests, but this appears 
to be mainly due to differences in head 
loss. Higher suspended-solid loading, 
entrained air (possibly enhanced by use 
of surfactant for oil breaking), and 
other factors could be responsible. 
Field tests were usually controlled to a 
lesser degree and generally gave slightly 
poorer results than laboratory tests. 
Filtrate volume at breakthrough for the 
MgO filter often doubled that for the 
sand filter, and F values were lower ex- 
cept for one test. Differences between 
dual-medium filters probably were not 
statistically significant, and run 
lengths were shortened considerably by 
early breakthrough. Although the field 
test results were for the most part not 
quite so good (higher F) as results from 



laboratory tests, the trends in the data 
are remarkably similar, and MgO is sub- 
stantially more effective than sand in 
this application. 

PROCESS WATER FROM MAGNETITE 
BENEFICIATION 

Process water used in the beneficia- 
tion of magnetite becomes laden with mod- 
erate levels of suspended hematite. 
Water is recycled and is treated only by 
settling before returning to the grinding 
circuit. As can be seen from the results 
of bench tests given in table 6, this 
water is easily filtered when 15 ppm alum 
is added for f locculation. MgO filters 
give slightly higher F values but more 
than double the filtrate volume of sand 
at breakthrough. Dual-medium anthracite- 
garnet and anthracite-MgO filters are 
nearly equivalent. Three field tests 
were run with single-medium MgO and sand 
filters, and the differences were even 
more pronounced than in the laboratory 
tests; breakthrough occurred so rapidly 
in the sand filters that quantitative 
comparisons were meaningless. Results 
for the MgO filters were comparable with 
those from bench tests. 



TABLE 6. - Filtration of iron ore processing water 



15 



Test 


Filter medium (d m ) 


T o» 
NTU 


t/t 


V, 
L/cm 2 


v, 

cm/s 


V/H 


F 
(xlO 5 ) 


49 

50 


1.3-mm anthracite, 0.71-mm MgO.... 
1.3-mm anthracite, 0.71-mm garnet. 
1.3-mm anthracite, 0.42-mm MgO.... 


49.5 
46.0 
54.5 
55.0 
56.0 


0.005 
.003 
.003 
.003 
.002 


4.0 
4.3 
8.3 
4.3 
11.2 


0.34 
.34 
.33 

.34 
.34 


220 

120 

990 

51 

21 


2.4 
2.2 

.26 
5.0 


51 


0. 7 1-mm MgO 


9.3 









PROCESS WATER FROM FLOTATION OF IRON ORE 

Process water from this flotation oper- 
ation had almost 250 ppm of very fine 
iron oxide and silicate particles, 11 ppm 
Ca hardness, 110 ppm dissolved Si0 2 , 
115 ppm P alkalinity, and 610 ppm M alka- 
linity (as milligrams of CaC0 3 ). This 
water is first settled in a large sedi- 
mentation basin and then clarified with 
alum flocculation before discharge. In 
these tests overflow from the sedimenta- 
tion basin was used to test the MgO and 
sand filters. 

Filteration results were extremely 
sensitive to flocculant dosage (Separan 
AP-30 anionic polymer), which was varied 
between 0.62 and 2.5 ppm. In general, 
sand outperformed MgO in field tests, 
giving F values that were 2.5 to 5 times 
lower than those for MgO. F(xl0 5 ) 
ranged from 470 to 1,300 for MgO and from 
200 to 290 for sand. These values are 
too high (high rate of head loss) to be a 
practical application for either filter 
medium. The results are consistent with 
other tests in which MgO filters became 
plugged easily when polymer flocculants 
were used. This type of process water 
needs to be softened and clarified before 
attempting filtration. 

MISSISSIPPI RIVER WATER 

Mississippi River water is used to sup- 
ply potable water to a large segment of 
the Minneapolis-St. Paul metropolitan 
area. Municipal-water treatment involves 
lime-softening, settling, and filtration 
followed by disinfection. A series of 
filtration tests were run on Mississippi 
River water treated in a manner similar 
to that used at the municipal water 
treatment plant. River water was first 
softened with 150 ppm CaO and then 



flocculated with 2.0 ppm alum. The 
decant after 15 to 30 min settling was at 
pH 8.0±0.5 and had turbidity of 35±2 NTU. 
More alum was mixed with the decant so 
that final alum concentration in the fil- 
ter influent was 26 ppm. Thirty- 
centimeter beds of sand and MgO were 
tested in parallel at a filtration veloc- 
ity of 0.21 cm/s. 

Three bench-scale tests were run under 
these conditions, and in two of the three 
tests run lengths were extended enough to 
reach breakthrough. Values of F(xl0 5 ) 
averaged 13±4 for the MgO and 22±12 for 
the sand. The main difference appears to 
be in the lower rate of head loss for the 
MgO, which averaged 1.7 times lower than 
for sand. The MgO filtered about 28 pet 
more water at breakthrough, based on the 
average of two tests. 

Since the minimum run length was al- 
ready about 11 h, both filters would 
operate at >95 pet availability, so the 
extra filtrate volume per cycle is proba- 
bly not too significant. The reduced 
head loss rate is an important advantage, 
however. 

PROCESS WATER FOR CUTTING GRANITE 

The final field tests were conducted on 
water used in cutting granite. 
Particulate-laden water is collected from 
all cutting and grinding stations and 
settled in a clarifier. Polymer is used 
to aid flocculation, but clarification is 
poor owing to inadequate control of floc- 
culant dosage, inadequate mixing, and 
convection due to evolution of gases 
caused by microbial activity. On occa- 
sion phosphoric acid (H3PO4 ) is also 
added to the system when a special kind 
of finish is being applied to the gran- 
ite. The process water is recycled with 
minimal makeup water; consequently, 



16 



hardness and conductivity are increased 
and calcite scaling and corrosion are 
serious operating problems. Zeta poten- 
tials of the suspended particles were 
found to be weakly negative, with values 
ranging from -1.4 to -23 mV with a mean 
value of -11±6 mV. The specific conduc- 
tivity was 1,300 ymho. 

These tests were intended to measure 
the filtering capability of the MgO over 
an extended period of time. Media attri- 
tion and scaling effects were to be ob- 
served directly, and their impact on fil- 
ter performance evaluated. Laboratory 
tests on process water samples indicated 
that MgO, sand, and anthracite were ap- 
proximately equal in their ability to 
filter this water. Both alum floccula- 
tion and softening the water by elevating 
pH were more effective than using poly- 
meric flocculants. 

In the field tests the water was 
treated first by softening with 6 pet 
NaOH and settling, and then by filtration 
through 55-cm beds of either 0. 71-mm MgO 
or sand. The NaOH solution was metered 
into raw process water entering a 570-L 
settler, and the overflow was kept at 



pH 9.0 to 9.8. Total flow through the 
system was 11.4 L/min (0.19 L/s), and the 
filtration velocity was 0.31 cm/s. Dual- 
medium filters were also tested with 1.3- 
mm anthracite replacing the upper 25 to 
30 pet of the beds. 

Laboratory tests varied considerably 
but generally indicated that F(xl0 5 ) 
values of around 30 could be expected in 
the field tests. Unfortunately, field 
test results varied even more than the 
laboratory tests. In some cases tur- 
bidity removal was excellent for both 
filters, and in other tests neither 
filter would perform efficiently. No 
trend could be discerned that would in- 
dicate that attrition was impairing MgO 
performance or that either sand or MgO 
was the better filter. Figure 4 illus- 
trates the wide variations in filtrate 
quality for tests with dual-medium 
filters. Curve 3 is a fairly typical 
plot for a good filtration run, in this 
case with the anthracite-MgO filter. 
Filtrate turbidity decreases below 1.0 
NTU within 1 h and remains low for a 
reasonable length of time. The anthra- 
cite-sand filter (curve 4) also achieved 



100.00 



CD 

=> 
I- 



.10 



.01 



1 

i 


1 


i 


i 


i 


i i 




~ //^--^SP^o. 


\^L 






/ 


KEY 
d Anthracite-MgO 
Anthracite-sand 
— * Samples taken 


- 


\. 


<? 








- 


< X. 


^^L, 




i 


















■Q--c>-^ t:> __ T3 __ a __ D J 




1 


i 


i 


i 


i 


i i 





4 
TIME, h 



FIGURE 4.— Filtration of granite-cutting process water. 



excellent turbidity removal after a 
longer delay. 

The arrows in figure 4 correspond to 
sampling for chemical analysis at the 
times shown. From the results given in 
table 7, it appears that good filtration 
resulted when P (probably as orthophos- 
phate) and Fe both were present in the 
process water. On the day that test 1 
was run both P and Fe levels were low and 
the anthracite-sand filtrate was turbid. 
After 5 h flow was switched to the 
anthracite-MgO filter, and turbidity re- 
moval was poor in the initial stages. 
Toward the end of the run, filtrate re- 
moval was improved and P and Fe were 
again both present at measurable levels. 
It is noteworthy that the MgO removes 
P and the sand does not. The MgO also 
adds small but significant amounts of Ca 
and Mg to that in the influent. (CaO is 



17 



an impurity in the periclase, present at 
1 to 3 wt pet. ) 

TABLE 7. - Chemical analysis of process 
water 



Stream 


pH 


Concentration, rc 


ig/L 




Ca 


Mg 


S 


P 


Fe 


Test 1: 














Influent. . 


9.3 


77 


57 


54 


<1.0 


1.7 


Filtrate. . 


9.3 


68 


55 


56 


<1.0 


<.2 


Test 2: 














Influent. . 


9.3 


71 


55 


60 


1.6 


3.0 


Filtrate. . 


9.4 


79 


66 


60 


<1.0 


<.2 


Test 3: 














Influent. . 


9.4 


64 


64 


69 


1.3 


2.3 


Filtrate.. 


9.5 


70 


71 


65 


<1.0 


<.2 


Test 4: 














Influent. . 


9.3 


69 


63 


66 


1.7 


.24 


Filtrate.. 


9.3 


65 


62 


56 


1.3 


3.1 



ENGINEERING ASPECTS 



BACKWASHING OF MgO FILTERS 

Filters are cleaned by backwashing with 
an upward flow of water, which fluidizes 
the bed and removes deposited solids 
mainly by hydraulic shearing forces. Of- 
ten air scouring is used to increase the 
backwash efficiency and reduce both the 
flow rate and flow volume required to 
clean the filter. The air bubbles in- 
crease abrasion between filter grains and 
give high shear rates owing to the in- 
creased turbulence in the bed. After 
dual-medium filters are backwashed with 
air scouring, a high-rate backwash is re- 
quired to restratify the media mixed by 
the vigorous cleaning action. Under- 
standing and being able to predict bed 
expansion are important for both the de- 
sign and operation of deep-bed filters. 
Ideally, it would be possible to calcu- 
late bed expansion for any flow velocity 
knowing only the basic properties of the 
filter medium and the fluid. In practice 
bed expansion can only be predicted from 
correlations derived from experimental 
data. It is also important to predict 
optimal backwash rates and to determine 
whether a desired combination of filter 



materials can be restratified by back- 
washing when used together in dual-medium 
filters. 

A filter bed becomes fluidized when the 
flow velocity is increased to the point 
where the head loss across the medium is 
equal to the weight of the grains in wa- 
ter. Further increases in flow velocity 
do not increase head loss across the bed; 
the bed expands and the increase in po- 
rosity offsets the higher velocity. A 
mass balance on the medium requires that 

h b (l- e ) = hb (l-e ), (3) 

where h b = bed depth, 

e = porosity, 

h bo = unfluidized bed depth, 

and e = unfluidized bed porosity. 

Bed porosity is observed to increase log- 
arithmically as a function of flow velo- 
city. In dimensionless form this is 
expressed as 

log Re = n log e + log Re| , (4) 



18 



where Re = 



Reynolds number, 
Re = (v d m /v), 



v = the fluid velocity, 

d m = the filter medium grain 
size, 

v = the kinematic viscosity of 
the fluid, 

and Re | = the Reynolds number corre- 
sponding to the unhindered 
settling velocity of the 
filter grains. 

As this velocity is approached, the me- 
dium is entrained in the fluid and the 
porosity becomes unity. Maximum shear 
rates occur at porosities between 0.68 
and 0.71 O0). 

The parameters n and Re | are obtained 
by measuring the initial-bed porosity or 
bulk density; for an arbitrarily chosen 
starting depth of medium, expanded bed 
height is measured at several flow veloc- 
ities. Expanded-bed porosity is calcu- 
lated from equation 3, and linear regres- 
sion or graphical methods are used to 
find the slope and intercept of plots of 
log e versus log v. This is repeated for 
various sizes of each medium. 

Both n and Re| are dependent on the 
fundamental dimensionless group known as 
the Archimedes or Galileo number: 



Ar = g d m 5 [(S.G.) m 



( S ' G -)f 1 , ( 5 ) 



where Ar = ratio of buoyant to viscous 
drag forces acting on a 
particle, 



(S.G.) f 
(S.G.) m 



g " 



d m = 



specific gravity of the 
fluid, 

specific gravity of the 
medium, 

the acceleration owing to 
gravity (9.8 m/s 2 ), 

the diameter of the grains 
of medium, 



and v = the kinematic velocity 
(m 2 /s). 

Ar incorporates only properties intrinsic 
to the medium and fluid. Values of Ar 
range from 10 2 to 10 5 for conventional 
deep-bed filters. 

Normal backwashing spans a transition 
region between laminar and turbulent 
flow, with Rej ranging from less than 10 
to approximately 500. One approach to 
modeling bed expansion is to use power- 
log correlations between n, Re] , and Ar 
for each medium: 

log n = ailog Re ( + bj (a^ <0) (6) 

log Rej = a2log Ar + b2« (7) 

This is successful if done within suffi- 
ciently narrow limits of Ar. For laminar 
or Stokes settling (Re <1), this simpli- 
fies to 



Re I = (const)Ar, 



(8) 



and for fully turbulent flow (Re >100), 
a] becomes very small and n approaches a 
constant value. Although accurate models 
can be obtained in this manner for a 
specific filter medium, attempts to make 
a more general model fail because there 
is no meaningful measure of particle 
shape and its effect on drag coefficient 

OO-n). 

A simple correlation was given by Bohm 
(12) for predicting the flow rate corre- 
sponding to maximum mass transfer rate in 
a fluidized bed: 



Re op+ = 0.072 Ar - 614 . 



(9) 



High shear rates enhance mass transfer by 
reducing the boundary layer thickness 
around the particles. Because large 
shear rates are also needed for cleaning 
deep-bed filters, this correlation may be 
useful for predicting optimum backwashing 
velocities. 

Fluidization curves for six sizes of 
MgO are shown in figure 5. Similar 
curves were obtained for sand and 



19 



10.00 




FIGURE 5 



0.60 0.70 

POROSITY U) 

—Bed expansion of MgO versus flow velocity. 



0.80 



olivine. Values of n and Re | were deter- 
mined by linear regression of the log e 
versus log v plots. Literature values 
for the viscosity and density of water 
were used to calculate Ar and Re at the 
temperatures measured during each test. 



Test results are summarized in table 8. 
Also included are values given by Gun- 
asingham (10) for anthracite, ballotini, 
polystyrene, and sand. ^ e pt was calcu- 
lated from equation 9 and then substi- 
tuted for Re in equation 4 to get E op -(-. 

Attempts to derive a specific model for 
the expansion of MgO were unsuccessful 
owing to the nonlinearity of plots of log 
n versus log Re j and log Re| versus log 
Ar. At grain sizes of 1 mm and greater, 
n varies much less than at the smaller 
sizes. Apparently there is a transition 
in the expansion behavior of MgO parti- 
cles between 0.5 and 1.0 mm. Data for 
sand also displayed nonlinear character- 
istics, but values for n agree fairly 
well with those of Gunasingham (10), con- 
sidering probable differences in particle 
shape and size distribution not taken in- 
to account. Because of these uncertain- 
ties, this type of correlation seems of 
limited value for design purposes. 

Calculated optimum bed porosities fall 
between 0.56 and 0.68 for particle sizes 
greater than 0.5 mm (fig. 6). Neglecting 
the lower e op ^ porosity values for ballo- 
tini and sand, the values for MgO, poly- 
styrene, and anthracite are between 0.65 
and 0.68, which is in good agreement with 
the predicted porosity range needed to 
produce maximum hydraulic shear (10). 
Ballotini and sand have smaller optimum 
porosities because they are more spheri- 
cal and have smaller initial porosities 
than MgO, anthracite, and polystyrene. 
Below 0. 5-mm grain size the optimum bed 
porosity is substantially greater than 
the predicted range for maximum shear. 
This is consistent with the data given 
by Bohm (12), which showed that, for 
Ar <10 3 , Re opt values begin to lie well 
below the correlation given by equation 
9. For nonspherical particles larger 
than 0.5 mm, the simpler correlation suc- 
cessfully predicts the optimum backwash 
velocity needed to achieve maximum shear 
rates. 

Determining the compatability of var- 
ious media for use in multimedium filters 
can be complicated. Intuitively it may 
be obvious that a separation will be 



20 



TABLE 8. - Fluidization results 



Sand: 

1. 54-mm 

1.00-mm 

. 71— mm 

.50-mm 

MgO: 

1. 54-mm 

1.30-mm 

1.00-mm 

.50-mm 

. 42-mm 

. 25-mm 

Olivine: 

0. 50-mm 

•35-mm 

. 25-mm 

Sand 00): 

0. 84-mm 

.65-mm 

. 42-mm 

Ballotini (10): 

2. 38-mm 

1. 30-mm 

. 92-mm 

• 78-mm 

Anthracite (10): 

2. 59-mm 

2. 38-mm 

1. 84-mm , 

1. 30-mm 

Polystyrene (10) 

3. 67-mm 

3.08-mm 

2. 59-mm , 

2. 18-mm 



Ar 



53,530 

15,497 

5,486 

4,727 

98,460 

58,690 

25,816 

3,218 

1,908 

402.5 

4,727 

1,667 

562 

7,935 
4,524 
1,184 

111,332 

25,659 

7,313 

5,221 

35,414 

21,418 

14,771 

4,948 

18,920 

14,724 

10,483 

7,409 



Re 



306 

178 
79.4 
50.4 

457 

332 

210 
77.7 
38.2 
11.0 

72.5 
38.7 
16.7 

95.7 
63.4 
27.1 

288 

134 
69.9 
56.1 

174.4 

133.7 

107.6 

60.2 

116.8 

102.9 

84.5 

69.1 



Re 



opt 



57.6 
26.9 
14.2 
13.0 

83.4 
61.0 
36.8 
10.3 
7.44 
2.86 

13.0 
6.85 
3.50 

17.9 
12.6 
5.55 

90.4 
36.7 
17.0 
13.8 

44.7 
32.8 
26.1 
13.4 

30.4 
26.1 
21.2 
17.1 



: opt 



0.56 
.56 
.57 
.69 

.65 
.65 
.65 
.67 
.74 
.79 

.74 
.82 
.83 

.65 
.67 
.68 

.59 
.59 
.58 
.58 

.66 
.66 
.68 
.67 

.65 
.65 
.66 
.66 



2.885 
3.220 
3.051 
3.607 

3.899 
3.875 
4.030 
5.057 
5.421 
5.645 

5.676 
8.098 
8.751 

3.873 
4.041 
4.162 

2.230 
2.429 
2.596 
2.611 

3.242 
3.417 
3.719 
3.795 

3.117 
3.180 
3.301 
3.420 



possible only if Re | of the upper medium 
is smaller than that of the lower layer. 
Re | also increases as a function of Ar, 
so it should be possible to predict sep- 
aration based on the size of Ar. In 
practice, however, this becomes compli- 
cated by differences in particle shapes 
and the fact that some intermixing of 
layers may be desirable. For convention- 
al filtration systems that operate with a 
downward flow, it is desirable to have 
the coarsest medium in the uppermost 
layer to achieve any benefit over 
single-medium filters. From this stand- 
point, a combination of MgO and sand is 
not a practical dual-medium filter. 



Attempts to backwash a filter with the 
upper layer of 0.71-mm sand and the lower 
layer of 0.5-mm MgO resulted in almost 
total intermixing of both layers. The 
corresponding values of Ar and Rej are 
very close (table 8). To get adequate 
differences in Re| would require either 
substantially finer MgO or at best equiv- 
alently sized sand as the upper layer, 
neither of which is desirable. 

MgO worked well with anthracite. Dual- 
medium filters of 0.71-mm MgO and 1.3-mm 
anthracite were easily restratified by 
backwashing. A sharp interface was pro- 
duced between the two media after 15 min 
of backwashing at flow velocities of 



21 



1.0 



.9 - 



.8 - 



00 

o 

JE .7 
o 

0_ 



.6 - 



- 


T ▼ 

• 

• T 


1 






1 


Elements 


1 
KEY 

Bureau of Mines 


Literature 




- 


MgO 

Sand 

Olivine 

Ballotini 

Polystyrene 

Anthracite 


• 

A 
▼ 

NA 
NA 
NA 


NA 

NA 
a 

O 


- 


▲ 














- 


- 


• 


A D O 

1 


5 " 

• 

□ 


• 
▲ 


I 


o o 
a 





- 



I 2 3 

FILTER GRAIN SIZE, mm 

FIGURE 6.— Optimum bed porosities calculated from optimum Reynolds number. NA = Not available. 



around 4 cm/s. Decreasing the velocity 
or duration of the backwash resulted in 
more intermixing of the two layers. An 
equivalently sized sand-anthracite filter 
was adequately but not so cleanly sepa- 
rated as the MgO-anthracite filter. 

ATTRITION OF MgO FILTERS DURING 
BACKWASHING 

Backwashing with air scour creates a 
significant amount of interparticle abra- 
sion in the filter medium. Although this 
is an effective backwashing technique, it 
does increase attrition of the filter me- 
dium. The rubbing action of the grains 
of filter medium produces fines that can 
clog the bed in subsequent filtrations 
and also reduce the effective size of the 
medium. High attrition rates can result 
in noticeable changes in filter perfor- 
mance; head-loss rates can increase 
enough to drastically reduce production 
of filtered water. Angular particles 
such as anthracite or MgO would be ex- 
pected to experience greater attrition 
than a spherical filter medium like sand. 

Forty-eight filtration cycles were made 
on a 61-cm bed of 0.71-mm MgO to test the 
resistance of the MgO filter grains to 
attrition. A standard suspension of 25 
ppm kaolin and 25 ppm milled sand, floc- 
culated with 10 ppm alum, and a filtra- 
tion velocity of 0.21 cm/s were used 
throughout. Each cycle consisted of a 
6-h filtration run followed by 1 h of 



backwashing. The backwashing proce- 
dure consisted of a few minutes of fluid- 
ization, followed by about 30 min of air- 
water scouring and then by 30 min of 
high-rate backwashing at 50-pct bed ex- 
pansion. This latter step was employed 
to remove fines and dislodge air bubbles. 
This backwashing procedure was actually 
more intense and longer in duration than 
that normally used in commercial prac- 
tice, since an air scour lasting 3 to 5 
min and a 10- to 15-min fluidization at 
20- to 50-pct bed expansion is usually 
sufficient to clean the bed (_9)» Total 
elapsed time for the 48 cycles to be com- 
pleted was about 6 months. The MgO fil- 
ter grains were kept under water in the 
filter column between cycles. 

Data from the initial, final, and every 
fifth intermediate run are listed in 
table 9. Cycle 39 was used in place of 

TABLE 9. - Durability study 



Cycle 


t/t q 


V/H 


F(xl0 5 ) 


SC, g/cm 3 




0.048 


190 


26 


9.0 




.081 


440 


19 


20 




.081 


590 


13 


27 


15 


.042 


640 


6.5 


31 


20 


.038 


440 


8.8 


21 




.046 


440 


11 


21 




.042 


341 


12 


16 


35 


.042 


296 


13 


14 




.042 


281 


15 


13 




.040 


326 


12 


16 


48 


.031 


297 


11 


14 



22 



cycle 40 because the latter had an unusu- 
ally large increase in head loss owing to 
air blinding of the filter. Variations 
in head loss rate account for most of the 
variation in the values of the filtration 
indexes. 

The solid-capture index, SC, is plotted 
versus the number of cycles in figure 7. 
Filter performance initially improves, 
then decreases gradually until a fairly 
stable value of SC is reached in the vi- 
cinity of the 40th cycle. Experimental 
uncertainty exists because low pressures 
and small pressure differences are dif- 
ficult to measure. Small pressure drops 
(head loss) for a bed result in high val- 
ues of SC. The uncertainity in measuring 
these small pressure drops leads to the 
large error brackets for SC values. In 
spite of the large uncertainty bracketing 
each point, the trend shown in figure 7 
appears to have statistical significance, 
and the value of SC near the end of 
the test has stabilized around 12 to 
15 g/cm 5 . The behavior of the filter- 
ability index [F(xl0 5 )] essentially mir- 
rors that of SC, and a stable level be- 
tween 10 and 15 is reached about halfway 
into the test. Values for F and SC com- 
pare quite favorably with those given in 
table 3 for filtration of kaolin and 
milled sand. 

Forty-eight backwash cycles is equiva- 
lent to a few weeks to several months of 




20 30 
FILTRATION CYCLES 



FIGURE 7.— Binding of MgO filters. 



operation, depending on the application. 
The intensity and duration of the air 
scour, which is largely responsible for 
filter grain attrition, is equivalent to 
a period of normal commercial operation 
perhaps 6 to 10 times longer. Since fil- 
tration performance of the MgO has stabi- 
lized at an acceptable value during these 
tests, attrition of MgO does not seem to 
be a significant problem. Media losses 
to attrition and entrainment in conven- 
tional media can be as high as 5 to 15 
wt pet in the first year of service 
(lower value for sand and higher value 
for anthracite). MgO losses are within 
this range; no significant decrease in 
bed depth was evident at the end of this 
test. 

MgO durability was also evaluated by a 
standard friability test used to evaluate 
filter media (13). Friability is deter- 
mined by calculating the fraction of sam- 
ple by weight that remains larger than 
the effective grain diameter (d e ff) after 
milling. Samples are milled by steel 
balls in a metal cylinder which is tum- 
bled end over end at 25 r/min for 15- and 
30-min intervals. The milled samples are 
sieved, and the weight in each size frac- 
tion is compared to initial weights in 
those size fractions. Losses of 6 to 
10 wt pet or less at 15-min milling and 
15 to 20 wt pet or less at 30-min milling 
of the filter material larger than d e ff 
indicate that the filter material has 
good durability. Attrition losses of 10 
to 15 wt pet and 15 to 25 wt pet for the 
two time intervals are tolerable for con- 
ventional filter media. A candidate fil- 
ter material is rejected if losses are 
>20 wt pet or >35 wt pet, respectively, 
for the two time intervals (13). MgO 
passed the standard friability test 
easily. A sample with an original d eff 
of 0.61 mm had losses of 4.0 wt pet and 
4.5 wt pet for the 15- and 30-min mill- 
ing. A second sample with d eff equal 
to 0.47 mm showed losses of 5.5 and 
7.0 wt pet for the two intervals. Both 
tests demonstrated very good durability 
for MgO. 



23 



POISONING OF MgO FILTERS BY HEAVY METALS 

Dissolved heavy metals present in the 
influent will encounter an increase in pH 
and may precipitate as they pass through 
an MgO filter. Previous experience in- 
dicated that these precipitates adhere 
quite strongly to MgO granules. This 
could spoil the desirable surface proper- 
ties of the MgO if the metal deposits are 
not removed by routine backwashing. If 
this were the case, it would become nec- 
essary to chemically strip the metals, 
most likely by adding either dilute acids 
or chelating agents at some stage in the 
backwashing. 

In this study a 46-cm bed of 0.5-mm MgO 
was tested using 25 ppm suspensions of 
kaolin, both with and without dissolved 
heavy metals being present. Influent pH 
was adjusted to 7.0±0.1 for all tests. 
The filter was put through a series of 
tests in which alternate filtrations were 
spiked with 5.0 ppm each of Cd 2+ , Mn 2 + , 



Ni 



2 + 



and 



Zn 2 \ 



all of which are 



soluble at neutral pH at this level of 
concentration. Between tests the filter 
was backwashed with air-water scouring, 
followed by fluidization at high flow 
velocity. Filtration velocity was 
0.34 cm/s. 

Plots of filtrate turbidity, pH, and 
pressure for these tests are plotted 
versus time in figure 8. In the first 
test cycle no metals were added and fil- 
trate pH remained fairly constant at 10.2 
to 10.3 for the 6-h test cycle. Head 
loss was small, and an average of 90 pet 
of the turbidity was removed. In the 
second test cycle heavy metals were in 
the influent. Turbidity was decreased by 
99 pet, but head loss increased dramati- 
cally. Coating of the MgO with precipi- 
tated metal hydroxides is indicated dur- 
ing this cycle by the steadily declining 
filtrate pH. Subsequent filtration with- 
out metals in the third test cycle showed 
a slight increase in the removal of tur- 
bidity and slightly lower filtrate pH 
than in the first test cycle. In the 



o 4 



2 E 



>- V) 

- o ° 

Q _J 



^ UJ 



■Cycle 



f\ 



\ 
\ 



\ 



\ 



V 



■Cycle 2- 




f^ 



-Cycle 3- 

KEY 
— pH 



Head loss 

Turbidity 



A 



\ 



\ 



\ 



< Cycle 5- 



_L 




10 



5 10 15 20 25 

TIME, h 

FIGURE 8.— Effects of dissolved heavy metals on MgO filtration. 



i 

Q. 
UJ 

1- 
< 
or 



30 



24 



fourth test cycle the dissolved metals 
were passed through the filter without 
the presence of kaolin. In this cycle 
the pH declined until it was only one 
unit higher than that of the influent, 
indicating that the reactive surface area 
of the MgO was virtually saturated with 
deposited precipitates of metal hydrox- 
ides. Head loss was large in this cycle, 
indicating that the precipitated metal 
hydroxides rather than flocculation of 
the kaolin were responsible for the in- 
creased resistance to flow observed in 
the second test cycle. In previous 
tests, flocculation was not observed in 
the reservoir containing the dissolved 
metals and kaolin suspension. In the 
fifth test cycle solid capture was again 
improved over that in the initial test; 
in fact, performance as measured by 



filtration indexes actually improved 
steadily with increased exposure to heavy 
metals. Values of F(xl0 5 ) for the first, 
third, and fifth runs were 28, 14, and 
3.0, and corresponding values for SC were 
7.8, 12, and 24 g/cm 3 . For the second 
test cycle, which had both metals and ka- 
olin present, F(xl0 5 ) was 60 and SC was 
3.5 g/cm 3 . It is concluded that heavy 
metals present in water to be filtered 
will be precipitated as hydroxides and 
will be bound to the MgO filter grains. 
These precipitated hydroxides are only 
partially removed by backwashing; how- 
ever, their presence on the MgO filter 
grains does not reduce the f ilterability 
of the MgO. Too high a level of heavy 
metals in the turbid water to be filtered 
will result in accelerated increases in 
head loss. 



FILTRATION PARAMETERS 



EFFECT OF SURFACE CHARGE AND PARTICLE 
SHAPE ON FILTRATION 

It has never been fully demonstrated to 
what effect the positive surface charge 
of the MgO contributes to its ability to 
remove particulate, although this has 
been previously suggested as a primary 
factor (_2~\3)« In early contact filtra- 
tion test studies, which used fine-mesh 
active MgO, surface charge interactions 
undoubtedly contributed greatly to the 
filtration of unf locculated asbestos fi- 
bers. But in applying this concept to 
practical deep-bed filtration, both sur- 
face area and activity were greatly re- 
duced in the transition. Deeper beds of 
coarse, dead-burned (fused) periclase 
were used instead of active (porous) MgO; 
furthermore, flocculation with aluminum 
salts was necessary to achieve efficient 
particulate removal. This would all tend 
to minimize any surface charge effect. 

The ultimate removal efficiency of a 
sand filter is equal to and sometimes 
slightly better than that of MgO, but the 
amount of material that can be collected 
(run length) of the MgO is often double 
that of sand. This can be partially ex- 
plained by the greater porosity of the 
MgO; more material can be deposited be- 
fore critical shear stresses are reached. 



Increased porosity means increased aver- 
age pore diameter, as would be the case 
in using a coarser filter medium. Cap- 
ture efficiency, however, usually de- 
creases as pore diameter increases. Some 
extra compensating mechanism allows the 
MgO to achieve removal rates nearly 
equivalent to those for sand. Surface 
charge and particle shape (altered hydro- 
dynamics) are two possible mechanisms. 

A factorial study was performed to 
qualitatively evaluate the effect of sur- 
face charge and grain shape on particle 
removal. Four combinations of medium 
shape and charge were tested using a 
standard pH 7.0 suspension of 50 ppm ka- 
olin with no flocculant. Shallow beds 
(15.2 cm) of 0.5-mm filter media were 
tested during 2-h runs. The size of the 
media tested is toward the small end of 
the sizes used in deep-bed filters. 

The four filter media were MgO (+, an- 
gular), sand (-, spherical), quartzite 
(-, angular), and MgO-coated sand 
(+, spherical). Zeta potentials were de- 
termined for crushed samples of media 
suspended in distilled water. The zeta 
potential of kaolin in distilled water 
was also measured and found to be -27±5 
mV. First-order removal coefficients 
were calculated from the ratio of influ- 
ent and filtrate turbidities: 



25 



TABLE 10. - Effects of filter medium surface charge and particle 
shape on kaolin removal 



Medium 


Zeta potential, 
mV 


No. of 
trials 


Removal coefficient, m" 1 




Xo 


Xf 


Angular shape: 
MgO 

Quartzite 

Spherical shape: 
MgO-coated sand 


20±7 
-28±3 

(+) 

-15±6 


4 
3 

! 3 

4 


7.5±0.6 
5.4±1.1 

7.9±1.8 
3.0± .6 


6.5±0.4 
11 ±1.5 

9.211.9 

8.4±1.3 



'The last trial was deleted because MgO coating was being lost. 
Values for X were much lower than for the other 3 trials. 



. _ In (t/tq) 

X " 1 



(10) 



Results are given in table 10. The 
clean-bed coefficient (X ) is based on 
the filtrate turbidities taken at 1 and 
15 min into the test, while the final 
turbidity (2 h) is used to calculate Xf . 

In the initial stages of filtration 
there was little deposited particulate, 
so particle-to-medium interactions should 
be at their maximum. Here MgO, whether 
as a spherical or an angular grain, is 
the most efficient filter by a substan- 
tial margin. The negatively charged 
media, whether angular or spherical, had 
lower removal efficiencies, but the mag- 
nitude of the (-) zeta potentials makes 
less difference than the shape of the 
medium; the more negative and angular 
quartzite is more effective than spheri- 
cal sand. The negative media exhibited 
increasing filtration efficiency with 
time; values of Xf are approximately 
double those of X . The MgO efficiency 
declines very slightly in this time; the 
MgO-coated sand efficiency increases, but 
with less than experimental uncertainty. 
Negatively charged media actually become 
the more efficient filters as deposits 
form in the filter owing to enhanced hy- 
drodynamic and mechanical interception 
mechanisms. Surface charge interactions 
were more important than shape for en- 
hancing clean-bed-particle collection. 
It is also of interest that head loss 
rates were lower for the positively 
charged media, averaging 3.5, 0, 5.3, and 
8.4 cm H 2 for the MgO, MgO-sand, sand, 
and quartzite, respectively. Unfortu- 
nately, the experimental uncertainty in 



pressure readings is at least 3.5 cm H 2 0, 
but it would seem that particle shape 
(hence bed porosity) alone is not totally 
responsible for observed head loss be- 
havior. It may be that different modes 
of particle deposition can significantly 
alter the development of head loss. Most 
deep-bed filters have coarser media, and 
flocculant is used to neutralize particle 
charge and increase particle size, so the 
surface charge of the medium is probably 
of little practical importance in operat- 
ing conventional deep-bed filters. 

REMOVAL AND HEAD LOSS COEFFICIENTS 

Empirical models have been used to de- 
scribe the head loss and filtrate quality 
as functions of time and filter-bed 
depth. The clean bed head loss can be 
calculated from the Kozeny-Carmen equa- 
tion (5): 



6H 
61 



5vV(l-e) 2 /6_\ 2 







ge 



(11) 



where 



H = head loss, 

1 = the filter depth, 

v = the kinetic viscosity, 

g = the gravitational 
acceleration, 

e = the bed porosity, 

v = the filtration velocity, 



26 



and d m = the grain size of the filter 
bed. 

A good filtration run exhibits a nearly 
linear increase in head loss with respect 
to time, which is closely approximated by 

H = H, + k H vC t, (12) 

where H = head loss, 

Hj = initial head loss, 

C Q = the influent concentration 
of suspended solids, 

t = the elapsed time, 

and kn = the head loss coefficient 
(cm 3 /g). 

This assumes particle removal rates of 
>99 pet. The head-loss coefficient is 
very similar to the SC index of equation 
2. The concentration profile with re- 
spect to depth has been modeled as a 
first-order process: 



$£- -AC 
61 XL > 



(13) 



where X is the removal coefficient (_5)» 
Concentration decreases logarithmically 
with depth as given in equation 10. A 
variety of other more complicated models 
are available for detailed analysis of 
deep-bed filters (6~_7)» To date, it has 
not been possible to predict these engi- 
neering parameters, which are useful in 
filter design, and thus they must be ob- 
tained, at least in part, by experiment 
(5-6). 

Beds of 0.5-mm sand and MgO were tested 
against 12.5-ppm kaolin suspensions at pH 
7.0±0.5. Flocculant was not used. Bed 
depths were varied between approximately 
5 and 50 cm. A water manometer was used 
rather than the usual pressure gauges to 
improve sensitivity and accuracy. (Pres- 
sure could be measured to ±2 mm H2O. ) 
For shallow beds, a known weight of fil- 
ter medium was used rather than attempt- 
ing to fill filter columns to a particu- 
lar depth, since variations in packing 
lead to relatively large changes in bed 



depth. Turbidity was used to calculate 
removal rate, and clean-bed-filter coef- 
ficients were calculated from the first 
two turbidity readings. Results are pre- 
sented in table 11. 

Attemtps to fit In (t/t ) as a linear 
function of depth were unsuccessful; al- 
though removal decreased with increasing 
depth, there was considerable random 
scatter around any type of linear plot. 
For this reason, values of X Q were merely 
tabulated and an average value given. 
Since turbidity removal was less than 
99 pet, SC was calculated rather than kg 
for head loss rate data. 

In general, the MgO filter gave slight- 
ly better removal rates and slightly low- 
er head loss rates than the sand filter. 
Results varied widely; the standard devi- 
ation of duplicate tests is 20 to 50 pet 
of mean values. It appears that SC val- 
ues improve for sand with increased bed 
depth, while values for MgO fluctuate 
randomly. Measurement uncertainties for 
turbidity and pressure are much smaller 
than the variation in results. Prepara- 
tion of suspensions is also carefully 
controlled, so it would seem that a fair 
amount of randomness is intrinsic to the 
process of deep-bed filtration. Packing 
irregularities may also be partially re- 
sponsible for the variability of results. 
Although these results are not quantita- 
tively precise, it can be seen that MgO 
does perform slightly better than sand 
without the intervening variable of 

TABLE 11. - Head loss and removal co- 
efficients of MgO and sand filters 
for the filtration of kaolin 



Bed depth 


A > 


F 


SC, 




cm" ' 


(xlO 5 ) 


g/cm 3 


MgO: 








9.2 cm. 


0.003 


44 


6.3 


18 cm. . 


.048 


18 


18 


36 cm. • 


1 .024 


134 


1 9.1 


46 cm. . 


.035 


29 


7.8 


Mean. . 


.03510.18 


36110.5 


9.414.6 


Sand: 








10 cm. . 


.017 


50 


3.3 


20 cm. . 


'.014 


1 56 


U.4 


40 cm. . 


.028 


34 


7.5 


Mean. . 


.01810.005 


491 8.3 


4.911.5 



'Average of 2 test values. 



27 



f locculation. These results are in qual- 
itative agreement with the bulk of the 
experimental data presented in this 
paper. 

pH AND CHEMICAL EFFECTS 

The major filtration characteristic of 
MgO, other than its positive surface 
charge, is its basicity. Unbuffered 
water passing over a bed of MgO will ex- 
perience an increase in pH of several un- 
its. At filtration velocities of 0.2 to 
0.3 cm/s, water entering a typical bed of 
periclase (inert MgO) at neutral pH will 
exit at pH 10 to 10.5. Salts of Al 3+ and 
Fe 3+ are amphoteric; consequently, a 
shift in pH could be expected to signifi- 
cantly alter their solubility. Both Al 3 + 
and Fe 3+ salts are common coagulants 
and/or flocculants used in water treat- 
ment to destabilize colloidal dispersions 
by neutralizing surface charge. Often 
relatively large quantities of Al 3 + or 
Fe 3+ are added to produce A1(0H) 3 or 
Fe(0H)3 floes that further clarify water 
by enmeshing particulates. Alum f loccu- 
lation was used in the majority of the 
filtration tests, and while this would 
tend to decrease favorable surface-charge 
interactions between particulates and 
MgO, the effect of pH could conceivably 
be important. Effects of pH generally 
were not investigated during previous 
filtration tests. 

A series of tests were run with 24-ppm 
kaolin suspensions in the presence of 
either 15 ppm Al 3+ as alum or 30 ppm Fe 3 + 
as FeCl3. This concentration of Al 3 + is 
about 5 to 20 times greater than those 
used in previous tests. (Concentrations 



were previously reported as ppm alum; 
formula weight is 474. ) Influent pH was 
varied between 4.5 and 7.0, and filtra- 
tion velocities were 0.33 to 0.35 cm/s. 
Results are given in table 12. A strong 
pH effect is evident for the Al 3+ -treated 
suspension, as turbidity removal is ob- 
served to be much poorer at higher in- 
fluent pH. At pH 6.9, removal is so poor 
that head loss is almost negligible; 
hence value of F is low. Fe 3+ removal is 
poor regardless of pH. Filtrate pH de- 
creases considerably throughout the test 
if alum is present, but changes very lit- 
tle with FeCl 3 . 

The differences in filtration results 
are probably due to the differences in 
solubility of the two salts. Al 3+ read- 
ily forms soluble hydroxy complexes, and 
the region of minimum solubility where 
A1(0H)3 formation predominates spans a 
fairly narrow pH range of 2 pH units cen- 
tered around pH 5. The solubility dia- 
gram of Fe 3+ is somewhat similar, though 
Fe(0H) 3 remains more insoluble over a 
much wider pH range; soluble hydroxy com- 
plexes are not formed appreciably between 
pH 3.5 and 13. Typical applications in 
water treatment use Al 3+ at pH 5 to 9 and 
Fe 3+ at pH 3 to 8 (L4). 

Apparently, efficient removal of the 
kaolin-Al suspension requires a certain 
amount of soluble Al to interact with the 
MgO surface. Sufficient soluble Fe is 
not available at these pH levels; conse- 
quently, bonding is poor and little 
kaolin-Fe suspension is retained. MgO is 
not likely to be used to collect Fe 3+ - 
flocculated suspensions in practice 
because dissolution of the MgO will 



TABLE 12. - Effect of influent pH on filtration of kaolin 
suspension flocculated with Al 3+ and Fe 3+ salts 



to. 

NTU 


t/t 


v, 
cm/s 


V, 
L/cm 2 


V/H 


F 
(xlO 5 ) 


Influent 
pH 


WITH 15 ppm Al 


35 


0.043 
.347 
.180 
.012 


0.340 
.347 
.330 
.349 


3.67 
2.50 
4.75 
5.02 


32.6 
1,010 
25.5 
14.9 


130 
34 

700 
82 


4.5 


23 


6.9 


27 


5.6 




4.5 


WITH 30 ppm Fe 


25 


0.221 
.370 


0.353 
.350 


1.27 
1.26 


36 
60 


610 
620 


6.7 




4.6 



28 



probably be excessive at pH levels much 
below 5.0. 

The mechanisms of these interactions 
are complex and further complicated by 
the fact that pH levels at the MgO sur- 
face are likely to be considerably higher 
than those of the bulk solution. The 
effect of pH on particle- and medium-sur- 
face charge would also have to be con- 
sidered. What effect pH had on filtra- 
tion tests with much smaller amounts of 
the Al is unclear, but it is probably at 
least as important as surface charge 
effects. 

SCALE FORMATION AND MUDBALLING 



scale-forming tendencies in the process 
water is recommended. 

Another type of cementation was ob- 
served in later tests at the same plant. 
Chunks of cemented MgO were again ob- 
served at the bottom of the filter bed. 
These were removed for inspection and are 
shown in figure 9. Their most interest- 
ing feature is the presence of grains of 
anthracite adhering to one side of the 
cemented chunks. Evidently these chunks 
formed at the MgO-anthracite interface 
and worked their way to the bottom of the 
filter during backwashing. These were 
probably formed as a result of com- 
pression of deposited solids at the 



Another consequence of the basicity of 
the MgO is scale formation. Water with 
appreciable calcium hardness and carbon- 
ate or phosphate alkalinity will form in- 
soluble calcium compounds due to the in- 
crease in pH. Cementation of MgO filters 
was observed in tests with several water 
samples. During backwashing, the medium 
tended to lift as a plug rather than 
fluidizing. Usually, air scour was 
enough to break up the scale and clean 
the filter. Formation of scale did not 
seem to seriously impair removal rates or 
cause excessively high head-loss rates 
during most filtration runs. 

Mudballing is one problem that can re- 
sult from scale formation in MgO filters. 
In conventional filter media, mudballing 
results from the compression of floccu- 
lated solids into a cake at the surface 
of the filter. The relatively large 
chunks of cake are not entrained in back- 
wash at practical fluidization rates. 
Depending on their size and density, 
these will either stay at the surface or 
sink to the bottom of the bed. In the 
field tests with the process water used 
for cutting granite, mudballing mani- 
fested itself differently. Cementation 
of the MgO was evident in the lower part 
of the filter, and although the bed was 
fluidized for the most part during back- 
washing, a rim of the cemented material 
remained along the outer edge at the bot- 
tom of the filter. This probably would 
be avoided if backwash air and water were 
better distributed at the bottom 
of the filter. However, control of 




FIGURE 9.— Cemented MgO chunks containing anthracite 
grains. 



29 



MgO-anthracite interface, but scale for- apparently 
mation may also be responsible. Sand tests, 
filters and sand-anthracite filters 



were not affected in these 



SUMMARY AND CONCLUSIONS 



Under the right circumstances MgO fil- 
ters offer significant advantages over 
similar conventional sand filters. Bu- 
reau results suggests that 0.5- to 0.71- 
mm MgO will filter water pretreated with 
alum better than equivalently sized par- 
ticles of conventional filter sand. Par- 
ticulate removal was approximately equal 
for the two media under these conditions, 
but much more water could be passed 
through the MgO filters before break- 
through. The porosity of the MgO filter 
bed is about 1.3 times greater than that 
of the sand filter bed, which probably 
accounts for its smaller rate of head 
loss and large run lengths before 
breakthrough. 

Current trends in conventional water 
treatment include the use of coarser me- 
dia in conjunction with polymer floccu- 
lants to increase solid-loading capacity. 
The floes created by polymer addition are 
more resistant to higher shear rates than 
alum floes; consequently, higher filtra- 
tion velocities are used. Excessive head 
loss rather than high turbidity tends to 
limit run length. Under these conditions 
MgO apparently offers little advantage 
over sand other than a slight reduction 
in head loss rate. 

In tests of recycled process water, 
elevated levels of dissolved solids usu- 
ally were found. The MgO filters were 
tolerant to moderate levels of calcium 
hardness and carbonate alkalinity, pro- 
vided adequate backwashing with air scour 
was available. 

No single solid removal mechanism can 
be definitively identified as the one re- 
sponsible for the improved filtration ob- 
served with granular MgO. In contact 
filtration of asbestos fibers, surface 
charge effects were almost certainly pre- 
dominant, but in shifting to granular MgO 
filters the specific surface area was 
greatly reduced and alum flocculation was 
necessary to achieve efficient solid re- 
moval. Both factors tend to indicate 
decreased importance of surface charge 



effects in comparison with mechanical ef- 
fects. pH-chemical effects may also be 
important. 

Granular MgO (periclase) possesses the 
necessary durability to be a filter me- 
dium; no drastic attrition effects were 
noticed in field tests or in laboratory 
longevity studies. MgO is also compat- 
ible with anthracite as a dual-medium 
filter, whereas sand-MgO filters are not 
likely to stratify in a workable manner 
except possibly in upflow filters. Bed 
poisoning by dissolved metals apparently 
is not a problem. 

Filtration is just one step in the 
overall water-treatment process. Optimi- 
zation of the clarification process will 
most likely outweigh optimization of the 
filtration process, since the former re- 
moves by far the larger amount of solids. 
In instances where mine and mineral- 
processing water is only moderately con- 
taminated by suspended solids, direct 
filtration of the mine water without 
clarification may be an attractive alter- 
native. A filter that can effectively 
remove suspended solids without pretreat- 
ment would be desirable. Comparison of 
filtration tests where 0.5-mm MgO is used 
to filter untreated kaolin and 0.71-mm 
MgO is used to filter alum-treated kaolin 
are encouraging. Solid capture indexes 
(SC) and f ilterability indexes (F) were 
better by almost an order of magnitude 
when no flocculant was added. Flocculant 
evidently adds considerable bulk to the 
suspended solids and contributes heavily 
to head loss. Reduced head loss is po- 
tentially the most beneficial advantage 
in employing MgO filtration. Rather than 
concentrating on comparing MgO and other 
media as conventional water filters, fu- 
ture research could explore the use of 
novel materials in novel filtration meth- 
ods. Various grades of MgO with interme- 
diate activity and hardness should be 
evaluated as filter media to determine 
whether the surface properties of MgO can 
be better utilized. 



30 



REFERENCES 



1. Schiller, J. E., and S. L. Payne. 
Surface Charge Measurements of Amphibole 
Cleavage Fragments and Fibers. BuMines 
RI 8483, 1980, 23 pp. 

2. Schiller J. E., and S. E. Khala- 
falla. Filtration of Asbestos and Other 
Solids With Magnesium Oxide. Min. Eng. 
(Littleton, CO), v. 35, No. 3, 1983, 
p. 237. 

3. Schiller, J. E., D. N. Tallman, 
and S. E. Khalafalla. Mineral Processing 
Water Treatment Using Magnesium Oxide. 
Environ. Progr. , v. 3, No. 2, 1984, 
pp. 136-141. 

4. Tallman, D. N. , and J. E. Shiller. 
Field Evaluations of Magnesium Oxide in 
Deep-Bed Filtration. BuMines RI 8936, 
1985, 11 pp. 

5. Ives, K. J. Deep Bed Filtration: 
Theory and Practice. Filtr. and Sep. , v. 
17, 1980, pp. 157-166. 

6. Tien, C, and A. C. Payatakes. 
Advances in Deep Bed Filtration. AIChE 
J., v. 25, No. 5, 1979, pp. 737-757. 

7. Rajagopulan, R. , and C. Tien. The 
Theory of Deep Bed Filtration. Ch. in 
Progress in Filtration and Separation, 
ed. by R. J. Wakeman. Elsevier, 1979, 
pp. 179-269. 

8. Lekkas, T. D. A Modified Filter- 
ability Index for Granular Bed Water 



Filters. Filtr. and Sep., v. 18, 1981, 
pp 214-216. 

9. Baumann, E. R. , and J. L. Cleasby. 
Waste Water Filtration Design Considera- 
tions. U.S. EPA Technol. Trans. Sem. 
Publ. EPA-624/4-74-007a, July 1974, 
36 pp. 

10. Gunasingham, K. , T. D. Lekkas, and 
T. J. Fox. Predicting the Expansion of 
Granular Filter Beds. Filtr. and Sep., 
v. 16, No. 6, 1983, pp. 619-623. 

11. Wakeman, R. J. Backwashing of 
Granular Filters. Ch. in Filtration 
Post-treatment Processes. Elsevier, 
1975, pp 138-145. 

12. Bohm, U. Maximum Mass Transfer to 
the Wall or Immersed Objects in Liquid 
Fluidized Beds. Ind. and Eng. Chem. Pro- 
cess Des. and Dev. , v. 22, No. 2, 1983, 
pp. 339-341. 

13. Degremont Co. Methods of Anal- 
ysis. Ch. in Wastewater Treatment Hand- 
book. Wiley, 5th ed. , 1979, 
pp. 940-944. 

14. Johnson, P. N. , and A. Aminthara- 
jah. Ferric Chloride and Alum as Single 
and Dual Coagulants. J. Am. Water Works 
Assoc, v. 75, No. 5, 1983, pp. 232-239. 



31 



APPENDIX. —NOMENCLATURE 
SYMBOLS 

a p radius of suspended particle, mm 

A r ratio of buoyant to viscous drag forces acting on a particle, dimensionless 

C suspended solids concentration in filtrate, mg/L 

C Q influent suspended solids concentration, mg/L 

d ef f effective grain diameter, mm 

d m diameter of the filter medium granules, mm 

dp diameter of particulate being filtered, mm 

e charge on an electron, eV 

F filterability index, dimensionless 

f subscript denoting fluid 

g acceleration due to gravity, 9.8 m/s 2 

H head loss, cm H 2 

h constant in London group, N l q5 dimensionless 

h b bed depth, m 

h bo bed depth of unfluidized bed, m 

Hj initial head loss, cm H2O 

k Boltzman's constant, cal/(mol*deg) 

k-H loss coefficient, cm 3 /g 

1 filter depth, m 

M represents metal 

m medium property 

m. molality of jth ion 

N DL double-layer filtration parameter 

N E i electronic group 1 filtration parameter 

N E 2 electronic group 2 filtration parameter 

N L0 London group filtration parameter 



250 87 &><* 



32 



Nr 

n g 

n 

P 

P e 

P 

R 

Re 

Re, 



Re 



opt 



SC 

S.G. 

T 

t 

V 



e opt 

Ed 



SYMBOLS — Continued 

relative size group filtration parameter 

gravity group filtration parameter 

parameter in Reynolds number determinations, dimensionless 

element symbol for phosphorus 

Pec let number 

particle property 

ideal gas law constant, 1.987 cal/(mol*deg) 

Reynolds number, dimensionless 

Reynolds number corresponding to unhindered settling of filter grains, 
dimensionless 

optimum Reynolds number, dimensionless 

solid capture index, g/cm 3 

specific gravity, g/cm 3 

absolute temperature, K 

time, h or s 

filtrate volume per unit area, L/cm 2 

filtration velocity, cm/s 

valence of jth ion 



differential notation 

porosity, dimensionless 

porosity of unfluidized bed, 
dimensionless 

optimum porosity, dimensionless 

dielectric constant of fluid, 
dimensionless 

inverse double-layer thickness, 



GREEK LETTERS 
v 



ir 

Pf 
Pp 



m 



-1 



To 



removal coefficient, cm -1 
viscosity, kg/(m*s) 



kinematic viscosity, u/p or m 2 /s 

constant, 3.1416 

density of fluid, kg/m 3 or g/cm 3 

density of particulate, kg/m 3 
or g/cm 3 

turbidity, NTU 

initial turbidity, NTU 

surface potential of filter 
medium, mV 

surface potential of 
particulate, mV 



US GOVERNMENT PRINTING OFFICE: 1987 605017/60052 



INT.-BU.OF MINES,PGH.,PA. 28502 



U.S. Department of the Interior 
Bureau of Mines— Prod, and Distr. 
Cochrans Mill Road 
P.O. Box 18070 
Pittsburgh, Pa. 15236 



OFFiCIAL BUSINESS 
PENALTY FOR PRIVATE USE WOO 

3 Do not wi sh to recei ve thi s 
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AN EQUAL OPPORTUNITY EMPLOYER 



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